Analytics Are Essential as Workload Automation Converges with Cloud Computing

Cloud computing has had a significant impact on all areas of IT, including workload automation (WLA). As cloud computing continues to shape the future of IT, WLA deployment increasingly aligns with the trend. More and more enterprises are running workloads in private or public clouds for additional capacity at peak times, permanent production jobs, singular workload tasks, etc. In a survey of over 400 IT and business professionals who work with WLA, Enterprise Management Associates (EMA) found that a slight majority of users host their WLA solution on-premises. However, this percentage has been decreasing the past few years and EMA believes private cloud will become the most common environment in which to run WLA software within the next three years.

It can be a challenge to maximize the efficiency of a hybrid computing environment, especially when workloads are spread across multiple vendors and platforms. Many organizations still use a variety of environments, some hosting legacy applications, and it is a continuous process to find the right mix of on-premises, private, and public cloud. Almost one third of those migrating WLA software in the past four years switched from on-premises to private cloud, according to EMA. This is a good indicator of the impact of cloud computing and the direction most are taking when placing WLA platforms. The growth of dynamic and hybrid computing environments leads to additional challenges in managing service levels and provisioning resources. This is why these environments need analytics to help drive them.

EMA also determined that the top three business reasons for using cloud resources for WLA are dynamic scalability, resource elasticity, and provisioning speed. Instead of investing in traditional IT infrastructure, companies can save money and more effectively manage the peaks and valleys of demand with the dynamism of a cloud. However, to fully realize these strategic benefits, companies need robust workload analytics. In an interview for The Silicon Review, Terma Software’s CEO Shane Hade provides an example of how analytics can help drive a dynamic computing environment: “For example, understanding a workload’s resource needs prior to and during execution requires predictive analytics to drive the provisioning mechanism and provide the right amount of computing resources.”

This kind of proactive workload management is possible with TermaANALYTICS! We can help you better understand, optimize, and manage your workload’s resource needs regardless of the complexity of your IT system and the environment where you host your WLA software. No matter the number or type of vendors, platforms, and computing environments, Terma Software’s workload analytics solution can normalize workload data to provide a comprehensive picture of your jobstreams. We have the flexibility to meet your needs with our own on-premises and cloud-based analytics offerings. Contact us to learn more about how we can help drive your hybrid computing environment.